Build Trust in Your Data for AI, BI, and Analytics Success
Organizations are increasingly turning to data-driven decision-making, yet data integrity remains a challenge. According to recent TDWI research:
- Only 50% of organizations trust their data.
- Despite recognizing data's value, only 50% have a formal data governance strategy in place.
Join us on March 19 to address these challenges and discover how to build a robust and trusted data foundation that powers business intelligence (BI), machine learning (ML), and artificial intelligence (AI) initiatives.
Register for Free and Build a Trusted Data Foundation
What You’ll Gain:
- 🚀 Cutting-Edge Insights – Discover the latest trends and solutions for meeting growing demands for data without creating bottlenecks, based on TDWI’s industry research.
- 💡 Inspiring Case Studies – Learn firsthand from organizations that have successfully provisioned data resources for use across their businesses.
- 🎯 Proven Best Practices – Gain actionable techniques to build a trusted data foundation for BI, machine learning, and AI while improving efficiency across teams.
- 🔑 Game-Changing Strategies – Master approaches to optimize your data architecture, accelerate delivery timelines, and support expanding use cases and audiences.
- 🛡️ Smart Governance – Implement governance frameworks that foster trust, ensure data reliability, and mitigate risks like data misuse or inconsistency.
Key topics will include:
- Data Integrity & Trust: Learn actionable strategies to improve data quality and build trust across your organization.
- Data Governance Best Practices: With governance ranking in the top 3 priorities for data management, you need to implement a strategy that ensures compliance, trust, and value.
- AI-Ready Data Foundations: Discover how to deliver data efficiently for AI models, BI applications, and self-service consumption.
- Scalable Data Architecture: Adapt your systems to support growing audiences, expanding analytics use cases, and AI demands.
- Operational Efficiency: Learn repeatable processes to streamline delivery and management of trusted data assets.